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Framework through which, given the model of any system consisting of an environment and the underlying mechanisms governing the functionality of any individual agent, a swarm is allowed to evolve behaviour genetically through mutations in it's neural network.
Creating neural networks with employed backpropagation and logistic sigmoid activation functions, mirroring the intricate interconnectivity of the human brain's neurons, pivotal for pattern recognition and classification.
Virtual creatures evolve to become the perfect bar crawlers! Have you ever wondered what the most efficient Durham bar crawl is? Sentient Crawlers has the answer!
A simple neural network library written in C++ for educational purposes. It provides basic functionality to create and train neural networks, including dense layers, activation functions, and backpropagation.